class_docstr: Databricks connectors are used to connect to Databricks Data Cloud.
docstr: Initialize the Databricks connector with the given configuration.
  
  Args:
      config (ConnectorConfig): The configuration for the Databricks connector.
docstr_tok: ["Initialize","the","Databricks","connector","with","the","given","configuration",".","Args",":","config","(","ConnectorConfig",")",":","The","configuration","for","the","Databricks","connector","."]
code: def __init__(self, config: Union[DatabricksConnectorConfig, dict]):
      """
      Initialize the Databricks connector with the given configuration.
  
      Args:
          config (ConnectorConfig): The configuration for the Databricks connector.
      """
      config["dialect"] = "databricks"
      if isinstance(config, dict):
          env_vars = {
              "token": "DATABRICKS_TOKEN",
              "database": "DATABRICKS_DATABASE",
              "host": "DATABRICKS_HOST",
              "port": "DATABRICKS_PORT",
              "httpPath": "DATABRICKS_HTTP_PATH",
          }
          config = self._populate_config_from_env(config, env_vars)
  
      super().__init__(config)
  
file_path: pandas-ai/pandasai/connectors/databricks.py
imports: from .base import BaseConnectorConfig, DatabricksConnectorConfig
  from sqlalchemy import create_engine
  from typing import Union
  from .sql import SQLConnector
label_desc: Use image node_id 1 to create a new DatabricksConnector object from inherited base classes: SQLConnector with example: obj = DatabricksConnector(config)